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DBMS > Datomic vs. GeoSpock vs. Google Cloud Datastore vs. Infobright vs. Vertica

System Properties Comparison Datomic vs. GeoSpock vs. Google Cloud Datastore vs. Infobright vs. Vertica

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfobright  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.datomic.comgeospock.comcloud.google.com/­datastoreignitetech.com/­softwarelibrary/­infobrightdbwww.vertica.com
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsvertica.com/­documentation
DeveloperCognitectGeoSpockGoogleIgnite Technologies Inc.; formerly InfoBright Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012200820052005
Current release1.0.6735, June 20232.0, September 201912.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava, JavascriptCC++
Server operating systemsAll OS with a Java VMhostedhostedLinux
Windows
Linux
Data schemeyesyesschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonononono
Secondary indexesyestemporal, categoricalyesno infoKnowledge Grid Technology used insteadNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)SQL-like query language (GQL)yesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsnousing Google App Enginenoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsnoCallbacks using the Google Apps Enginenoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersAutomatic shardingShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using PaxosSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnonoyesno
User concepts infoAccess controlnoAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicGeoSpockGoogle Cloud DatastoreInfobrightVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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DatomicGeoSpockGoogle Cloud DatastoreInfobrightVertica infoOpenText™ Vertica™
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